AWS AI Practitioner vs Azure AI-900 vs GCP MLE: Which AI Certification Should You Get First?

AWS AI Practitioner (AIF-C01) and Azure AI Fundamentals are both entry-level AI certifications. AIF-C01 is a 90-minute, 65-question exam that costs USD 100 and is valid for 3 years. Azure AI Fundamentals now uses exam AI-901, which replaced AI-900 on June 30, 2026, and its price depends on your country.

Practice this exam in timed mode with the StudyKits Professional Machine Learning Engineer app. All guides and practice apps for these vendors are on the AWS certification hub, Google Cloud certification hub.

Google Cloud’s Professional Machine Learning Engineer (PMLE) is a different tier: a 2-hour professional exam for people who already build ML systems. Pick the entry exam for the cloud you use at work; take PMLE once you have hands-on ML experience.

All exam facts below come from the vendor pages listed under Sources, checked October 15, 2026.

How do the three AI certifications compare at a glance?

Feature	AWS AI Practitioner (AIF-C01)	Azure AI Fundamentals (AI-901)	Google Cloud PMLE
Level	Foundational	Fundamentals	Professional
Target audience	People who use AI/ML on AWS	Early-career AI solution developers	Experienced ML engineers
Recommended background	Familiar with AI/ML on AWS; does not need to build models	Python syntax and basic Azure resources	3+ years in industry, 1+ year on Google Cloud
Number of questions	65 (50 scored + 15 unscored)	Not stated on the certification page	50-60
Time limit	90 minutes	Not stated on the certification page	2 hours
Passing score	700 (scaled 100-1,000)	Not stated on the certification page	Not published
Exam cost	USD 100	Set by country or region	USD 200 (plus tax)
Validity	3 years	See Microsoft Learn	2 years
Key focus	Generative AI, foundation models, responsible AI	AI concepts, Microsoft Foundry	ML system design, pipelines, monitoring

Is AWS AI Practitioner or Azure AI Fundamentals easier?

Both are entry exams, so neither expects you to train models. The difference is in what they ask you to know.

Azure AI Fundamentals (AI-901)

Microsoft lists two skill areas for AI-901: “Identify AI concepts and capabilities” and “Implement AI solutions with Microsoft Foundry”. The certification page also asks for knowledge of Python syntax and familiarity with Azure resources. That is a change from AI-900, which had no coding expectation.

If you have never worked with AI or cloud services, expect to learn Python basics as well as AI concepts.

AWS AI Practitioner (AIF-C01)

AIF-C01 has five domains. Applications of Foundation Models is the largest at 28%. Fundamentals of Generative AI is 24%, and Fundamentals of AI and ML is 20%. Guidelines for Responsible AI and Security, Compliance, and Governance for AI Solutions are 14% each.

The exam includes ordering and matching items as well as multiple choice. AWS describes the candidate as someone who uses AI/ML on AWS but does not necessarily build it.

For the next step after AIF-C01 on AWS, read MLA-C01 or AIP-C01: which first?.

Google Cloud Professional Machine Learning Engineer

PMLE is a professional exam. Google recommends 3+ years of industry experience, including 1+ year designing and managing solutions on Google Cloud. The current guide is dated June 1, 2026.

It covers low-code AI, data and model collaboration, scaling prototypes, serving, pipelines and monitoring. The guide reflects the move from Vertex AI to Gemini Enterprise Agent Platform. Hands-on experience matters more here than for the other two.

What does each exam test?

AWS AI Practitioner (AIF-C01)

• Fundamentals of AI and ML (20%)
• Fundamentals of generative AI (24%)
• Applications of foundation models, including prompts and RAG (28%)
• Guidelines for responsible AI (14%)
• Security, compliance, and governance for AI solutions (14%)

Azure AI Fundamentals (AI-901)

• Identify AI concepts and capabilities
• Implement AI solutions with Microsoft Foundry

Google Cloud Professional ML Engineer (guide as of June 1, 2026)

• Architecting low-code AI solutions (~13%)
• Collaborating within and across teams to manage data and models (~16%)
• Scaling prototypes into ML models (~21%)
• Serving and scaling models (~20%)
• Automating and orchestrating ML pipelines (~18%)
• Monitoring AI solutions (~13%)

Which certification helps your salary more?

No vendor publishes salary data for these exams. In general, a professional-level credential like PMLE signals more than a fundamentals credential, but experience counts for more than either.

For how we read salary surveys, see the AI and cloud certification salary guide.

Which certification fits your career?

Choose AWS AI Practitioner (AIF-C01) if

• Your organization runs on AWS, or you want to work at one that does
• You work with AI as a developer, analyst, product manager or consultant, but do not build models
• You plan a later AWS step such as Machine Learning Engineer - Associate or Generative AI Developer - Professional

Choose Azure AI Fundamentals (AI-901) if

• Your organization is a Microsoft shop
• You are early in an AI developer career and comfortable learning some Python
• You plan to take a role-based Azure AI certification next

StudyKits has no app for AIF-C01 or AI-901.

Choose Google Cloud PMLE if

• You have several years of hands-on ML engineering experience
• You work with, or plan to work with, Google Cloud
• You want to show professional-level ML skills rather than learn fundamentals

Should the cloud platform decide?

Yes, in most cases. A certification on the platform you use at work helps you every day; one on a platform you never touch mostly decorates a CV.

If you have no platform yet, look at job ads in your area and count which cloud they ask for. For a broader view across all three providers, see AWS vs GCP vs Azure certifications.

In what order should you take several AI certifications?

Path A: no AI experience yet

1. AWS AI Practitioner (AIF-C01) or Azure AI Fundamentals (AI-901), whichever matches your cloud
2. The other entry exam, if you work across both clouds
3. Google Cloud PMLE, after you have built and deployed ML systems

Path B: some AI/ML experience

1. AWS AI Practitioner (AIF-C01)
2. Google Cloud PMLE
3. A role-based Azure AI certification, if you work in Microsoft environments

Path C: experienced ML engineer

1. Google Cloud PMLE
2. AWS Machine Learning Engineer - Associate or Generative AI Developer - Professional (AIP-C01)
3. AWS AI Practitioner, only if an employer asks for it

How should you study and practise for each?

Factor	AWS AIF-C01	Azure AI-901	Google Cloud PMLE
Free vendor training	AWS Skill Builder	Microsoft Learn	Google Skills
Official practice	AWS Skill Builder	Practice Assessment on AI Skills Navigator	Exam guide (see Sources)
Hands-on labs	Helpful	Helpful, with some Python	Essential
StudyKits app	None	None	PMLE app

The StudyKits PMLE app’s questions follow the previous exam outline; update in progress.

Frequently asked questions

Is AI-900 still available?

No. Microsoft retired AI-900 on June 30, 2026. Azure AI Fundamentals now requires exam AI-901.

Is AWS AI Practitioner the same as AWS Generative AI Developer?

No. AI Practitioner (AIF-C01) is foundational, 90 minutes, USD 100. Generative AI Developer - Professional (AIP-C01) is a 180-minute professional exam that costs USD 300.

Which is better: AWS Cloud Practitioner or AI Practitioner?

They test different things. Cloud Practitioner (CLF-C02) covers AWS cloud basics and billing. AI Practitioner covers AI, generative AI and responsible AI. Both cost USD 100 and pass at 700.

Do I need coding for these exams?

AIF-C01 does not expect you to build models. AI-901 asks for Python syntax knowledge. PMLE expects real ML engineering work.

Sources

Checked October 15, 2026:

• AWS Certified AI Practitioner exam page
• AWS AIF-C01 exam guide
• AWS Certified Generative AI Developer - Professional exam page
• Microsoft Learn: Azure AI Fundamentals
• Microsoft Learn: Exam AI-900 (retirement notice)
• Google Cloud Professional Machine Learning Engineer
• Google Cloud certification renewal FAQ